Site,trigger, quenching mechanism and recovery of non-photochemical quenching in cyanobacteria: recent updates

Femtosecond transient absorption was used to study excitation decay in monomeric and trimeric cyanobacterial Photosystem I (PSI) being prepared in three states: (1) in aqueous solution, (2) deposited and dried on glass surface (either conducting or non-conducting), and (3) deposited on glass (conducting) surface but being in contact with aqueous solvent. The main goal of this contribution was to determine the reason of the acceleration of the excitation decay in dried PSI deposited on the conducting surface relative to PSI in solution observed previously using time-resolved fluorescence (Szewczyk et al., Photysnth Res 132(2):111–126, 2017). We formulated two alternative working hypotheses: (1) the acceleration results from electron injection from PSI to the conducting surface; (2) the acceleration is caused by dehydration and/or crowding of PSI proteins deposited on the glass substrate. Excitation dynamics of PSI in all three types of samples can be described by three main components of subpicosecond, 3–5, and 20–26 ps lifetimes of different relative contributions in solution than in PSI-substrate systems. The presence of similar kinetic components for all the samples indicates intactness of PSI proteins after their deposition onto the substrates. The kinetic traces for all systems with PSI deposited on substrates are almost identical and they decay significantly faster than the kinetic traces of PSI in solution. We conclude that the accelerated excitation decay in PSI-substrate systems is caused mostly by dense packing of proteins.     

Improved photosynthetic characteristics correlated with enhanced biomass in a heterotic F1 hybrid of maize (Zea mays L.)

Photosynthesis Research - Heterosis is a phenomenon wherein F1 hybrid often displays phenotypic superiority and surpasses its parents in terms of growth and agronomic traits. Investigations on the...     

Improved Working Memory but No Effect on Striatal Vesicular Monoamine Transporter Type 2 after Omega-3 Polyunsaturated Fatty Acid Supplementation

Studies in rodents indicate that diets deficient in omega-3 polyunsaturated fatty acids (n–3 PUFA) lower dopamine neurotransmission as measured by striatal vesicular monoamine transporter type 2 (VMAT2) density and amphetamine-induced dopamine release. This suggests that dietary supplementation with fish oil might increase VMAT2 availability, enhance dopamine storage and release, and improve dopamine-dependent cognitive functions such as working memory. To investigate this mechanism in humans, positron emission tomography (PET) was used to measure VMAT2 availability pre- and post-supplementation of n–3 PUFA in healthy individuals. Healthy young adult subjects were scanned with PET using [¹¹C]-(+)-α-dihydrotetrabenzine (DTBZ) before and after six months of n–3 PUFA supplementation (Lovaza, 2 g/day containing docosahexaenonic acid, DHA 750 mg/d and eicosapentaenoic acid, EPA 930 mg/d). In addition, subjects underwent a working memory task (n-back) and red blood cell membrane (RBC) fatty acid composition analysis pre- and post-supplementation. RBC analysis showed a significant increase in both DHA and EPA post-supplementation. In contrast, no significant change in [¹¹C]DTBZ binding potential (BP_ND) in striatum and its subdivisions were observed after supplementation with n–3 PUFA. No correlation was evident between n–3 PUFA induced change in RBC DHA or EPA levels and change in [¹¹C]DTBZ BP_ND in striatal subdivisions. However, pre-supplementation RBC DHA levels was predictive of baseline performance (i.e., adjusted hit rate, AHR on 3-back) on the n-back task (y = 0.19+0.07, r² = 0.55, p = 0.009). In addition, subjects AHR performance improved on 3-back post-supplementation (pre 0.65±0.27, post 0.80±0.15, p = 0.04). The correlation between n-back performance, and DHA levels are consistent with reports in which higher DHA levels is related to improved cognitive performance. However, the lack of change in [¹¹C]DBTZ BP_ND indicates that striatal VMAT2 regulation is not the mechanism of action by which n–3 PUFA improves cognitive performance.     

Parkinson’s disease: what the model systems have taught us so far

Parkinson’s disease (PD) is a debilitating neurodegenerative disorder, for which people above the age of 60 show an increased risk. Although there has been great advancement in understanding the disease-related abnormalities in brain circuitry and development of symptomatic treatments, a cure for PD remains elusive. The discovery of PD associated gene mutations and environmental toxins have yielded animal models of the disease. These models could recapitulate several key aspects of PD, and provide more insights into the disease pathogenesis. They have also revealed novel aspects of the disease mechanism including noncell autonomous events and spreading of pathogenic protein species across the brain. Nevertheless, none of these models so far can comprehensively represent all aspects of the human disease. While the field is still searching for the perfect model system, recent developments in stem cell biology have provided a new dimension to modelling PD, especially doing it in a patient-specific manner. In the current review, we attempt to summarize the key findings in the areas discussed above, and highlight how the core PD pathology distinguishes itself from other neurodegenerative disorders while also resembling them in many aspects.     

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration.     

Plant phylogeny drives arboreal caterpillar assemblages across the Holarctic

1. Assemblages of insect herbivores are structured by plant traits such as nutrient content, secondary metabolites, physical traits, and phenology. Many of these traits are phylogenetically conserved, implying a decrease in trait similarity with increasing phylogenetic distance of the host plant taxa. Thus, a metric of phylogenetic distances and relationships can be considered a proxy for phylogenetically conserved plant traits and used to predict variation in herbivorous insect assemblages among co‐occurring plant species.
2. Using a Holarctic dataset of exposed‐feeding and shelter‐building caterpillars, we aimed at showing how phylogenetic relationships among host plants explain compositional changes and characteristics of herbivore assemblages.
3. Our plant–caterpillar network data derived from plot‐based samplings at three different continents included >28,000 individual caterpillar–plant interactions. We tested whether increasing phylogenetic distance of the host plants leads to a decrease in caterpillar assemblage overlap. We further investigated to what degree phylogenetic isolation of a host tree species within the local community explains abundance, density, richness, and mean specialization of its associated caterpillar assemblage.
4. The overlap of caterpillar assemblages decreased with increasing phylogenetic distance among the host tree species. Phylogenetic isolation of a host plant within the local plant community was correlated with lower richness and mean specialization of the associated caterpillar assemblages. Phylogenetic isolation had no effect on caterpillar abundance or density. The effects of plant phylogeny were consistent across exposed‐feeding and shelter‐building caterpillars.
5. Our study reveals that distance metrics obtained from host plant phylogeny are useful predictors to explain compositional turnover among hosts and host‐specific variations in richness and mean specialization of associated insect herbivore assemblages in temperate broadleaf forests. As phylogenetic information of plant communities is becoming increasingly available, further large‐scale studies are needed to investigate to what degree plant phylogeny structures herbivore assemblages in other biomes and ecosystems.

     

Prioritizing Tiger Conservation through Landscape Genetics and Habitat Linkages

Even with global support for tiger (Panthera tigris) conservation their survival is threatened by poaching, habitat loss and isolation. Currently about 3,000 wild tigers persist in small fragmented populations within seven percent of their historic range. Identifying and securing habitat linkages that connect source populations for maintaining landscape-level gene flow is an important long-term conservation strategy for endangered carnivores. However, habitat corridors that link regional tiger populations are often lost to development projects due to lack of objective evidence on their importance. Here, we use individual based genetic analysis in combination with landscape permeability models to identify and prioritize movement corridors across seven tiger populations within the Central Indian Landscape. By using a panel of 11 microsatellites we identified 169 individual tigers from 587 scat and 17 tissue samples. We detected four genetic clusters within Central India with limited gene flow among three of them. Bayesian and likelihood analyses identified 17 tigers as having recent immigrant ancestry. Spatially explicit tiger occupancy obtained from extensive landscape-scale surveys across 76,913 km² of forest habitat was found to be only 21,290 km². After accounting for detection bias, the covariates that best explained tiger occupancy were large, remote, dense forest patches; large ungulate abundance, and low human footprint. We used tiger occupancy probability to parameterize habitat permeability for modeling habitat linkages using least-cost and circuit theory pathway analyses. Pairwise genetic differences (F _ST) between populations were better explained by modeled linkage costs (r>0.5, p<0.05) compared to Euclidean distances, which was in consonance with observed habitat fragmentation. The results of our study highlight that many corridors may still be functional as there is evidence of contemporary migration. Conservation efforts should provide legal status to corridors, use smart green infrastructure to mitigate development impacts, and restore habitats where connectivity has been lost.